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Prediction of Battery Behavior Subject to High-Rate Partial State of Charge
An online optimization procedure provides the parameters of a nonlinear battery model by taking into account a few minutes of measured current-voltage data. Within a defined range in terms of charge current, state of charge (SOC), and duration of charge and discharge events, the model is able to cap...
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Published in: | IEEE transactions on vehicular technology 2009-02, Vol.58 (2), p.588-595 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | An online optimization procedure provides the parameters of a nonlinear battery model by taking into account a few minutes of measured current-voltage data. Within a defined range in terms of charge current, state of charge (SOC), and duration of charge and discharge events, the model is able to capture the relevant battery dynamics and predict the behavior for the next few minutes. From the battery behavior during specific events, the state of the battery can be revealed, which is defined as the state of function. Validation, which is carried out on measured current-voltage profiles, shows the accuracy of prediction during the high-rate partial SOC operation. Even with the data measured during a city drive within a microhybrid electrical vehicle, the method is able to predict the voltage level during high-rate discharge pulses (cranking).cranking |
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ISSN: | 0018-9545 1939-9359 |
DOI: | 10.1109/TVT.2008.928005 |